Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Static gesture identification method

A gesture recognition and gesture technology, which is applied in character and pattern recognition, instruments, computer parts, etc., can solve the problem of low recognition rate and achieve high recognition rate and improved recognition speed

Active Publication Date: 2014-10-15
UNIV OF JINAN
View PDF3 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Yang Bo et al. proposed a gesture recognition algorithm with spatial distribution features, which combined the overall appearance features of the gesture with the joint change characteristics of the gesture to extract the spatial distribution feature (HDF) of the gesture. This method has a higher accuracy for gestures with large differences. Recognition rate, but for gestures with less discrimination, the recognition rate is not high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Static gesture identification method
  • Static gesture identification method
  • Static gesture identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0023] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0024] A static gesture recognition method of the present invention first starts a camera to acquire a BMP image of a current frame containing a target gesture. In order to make the gesture recognition unaffected by the size of the gesture, the gesture image is first standardized, that is, the image size is unified to the same size (40*40 image size is used). Firstly, the gesture is segmented from the background image with the skin color distribution model, and then the segmented gesture image is standardized.

[0025] The steps of image normalization processing are as follows:

[0026] Input: Segmented gesture images.

[0027] Output: Normalized gesture images.

[0028] Step1. Find the smallest circumscribed square of the gesture image.

[0029] Step2. Scale the gesture image in the square to a size of 40*40 according to the scaling formula (1).

[0030] ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a static gesture identification method. The invention provides a gesture identification method based on HCDF (Hand Coordinate Distribution Feature) and similar-Hausdorff distance template matching. The static gesture identification method comprises the following steps: firstly, extracting a gesture feature vector by HCDF; then, carrying out similarity measurement to the extracted feature and a sample library to select M types of similar candidate samples; and finally, identifying a final gesture from the M types of similar candidate samples by the thought of the similar-Hausdorff distance template matching. The invention has beneficial effects that the static gesture identification method exhibits a higher identification rate if the static gesture identification method is compared with a HDF (Hand Distribution Feature), can accurately identify gestures of rotation, zoom and translation and still keeps the high identification rate for similar gestures with a small distinction degree. In addition, compared with a method that only the similar-Hausdorff distance is used for identification, the static gesture identification method is characterized in that identification speed is greatly quickened.

Description

technical field [0001] The invention relates to a static gesture recognition method. Background technique [0002] As a novel means of human-computer interaction, gesture interaction has become a research hotspot in the field of human-computer interaction in recent years. Vision-based gesture recognition is an indispensable key technology for gesture interaction. From the motion characteristics of gestures, vision-based gesture recognition can be divided into two categories: dynamic gesture recognition and static gesture recognition. Dynamic gesture can be defined as the trajectory of hand movement, which means that the shape and position of the gesture change with time. Therefore, the recognition effect is easily affected by factors such as gesture contour, spatio-temporal position, and moving rate. Static gestures can be considered as a special case of dynamic gestures at a certain point in time, and refer to gestures that do not change over time, and their recognition e...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46
Inventor 冯志全杨学文
Owner UNIV OF JINAN
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com